
Explore three effective form tracking techniques using Google Tag Manager and Google Analytics, including URL success page, form submit trigger, and element visibility trigger.

Learn to implement an abandoned cart email campaign using Google Tag Manager and Klaviyo, tracking user actions and creating targeted email sequences to boost conversions.

Comprehensive overview of gtag.js, exploring its features, pros and cons, implementation scenarios, and comparison with Google Tag Manager for effective website tracking and analytics.

Learn to track element visibility and DOM changes using Google Tag Manager's new trigger, enhancing your ability to monitor user interactions and page elements dynamically.

Learn to implement YouTube video tracking on your website using Google Tag Manager's new YouTube Trigger for enhanced analytics and progress monitoring.

Explore Yandex Metrica as a potential Google Analytics alternative, comparing features like dashboards, bounce rate, goals, and session replay to help you make an informed decision.

Learn to efficiently manage electronic component lists, BOMs, and orders with Digi-Key's myLists feature. Master uploading, customizing, and organizing parts for streamlined purchasing and quoting processes.

Renowned AI expert Michael Jordan discusses the future of machine learning, exploring potential billion-dollar industries and addressing key challenges in the field of data science and AI.

Data science strategies for global risk mitigation: standardized frameworks, scaling solutions, market size management, model monitoring, cloud variability, agility, and cross-geographic data governance.

Explore strategies for building an effective data science team that leverages automation, balancing skilled professionals and citizen data scientists for successful AI implementation.

A framework for data science project managers covering team formation, analytical solution processes, and risk management. Focuses on effective project execution rather than specific algorithms.

Blend data science with design thinking to create AI/ML products that prioritize customer needs, using empathy, experimentation, and rapid prototyping for optimal user experience.

Explore common pitfalls in mission analytics and learn strategies to avoid them, focusing on mindset shifts, talent mix, project phasing, and scaling challenges in data-driven organizations.

Explore bias in AI vision and language with Margaret Mitchell, focusing on ethical concerns, societal impacts, and strategies for developing more inclusive and fair artificial intelligence systems.

Explore data-efficient solutions for supply chain management, focusing on forecasting with limited data and making robust decisions in complex, dynamic systems.

Explore the evolution from Big Data to Data Science with Usama Fayyad, focusing on predictive analytics in a changing data landscape and its impact on business growth and competitive advantage.

Explore machine learning with scikit-learn: its popularity, capabilities, and future. Learn about easy predictive analysis, development process, and exciting new features in this data science ecosystem.

Explore healthcare predictive analytics with Evariant and DataRobot. Learn about propensity models, evolving solutions, and best practices for targeted marketing in medical campaigns.

Explore data-driven hiring for data scientists, focusing on innovative screening processes that filter for skills and talent rather than keywords, to find the best candidates efficiently.

Explore big data machine learning with Python and H2O in this talk. Learn about H2O's distributed processing, integration with Python ecosystem, and fast production scoring for smart business applications.

Learn to develop propensity models for targeted marketing campaigns in e-commerce using machine learning algorithms. Discover key drivers of customer data to predict subscription probability and improve conversion rates.